SINGLE-PASS SEA/ICE DISCRIMINATION USING ERS-2 SCATTEROMETER DATA

This paper presents a new method to perform sea/ice discrimination in single-pass ERS-2 scatterometer data. Existing methods are 1rst reviewed and compared in a consistent framework. Next, the ice probability according to the individual existing methods is learned through the use of a neural network...

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Bibliographic Details
Main Authors: Xavier Neyt, Pauline Pettiaux, Nicolas Manise, Marc Acheroy
Format: Article in Journal/Newspaper
Language:English
Spanish
Published: Universidad de Concepción 2004
Subjects:
Scatterometry
ice discrimination
neural network
Oceanography
GC1-1581
Zoology
QL1-991
Sea ice
Online Access:https://doaj.org/article/281beb98124f4720bdf88dd31b75f4fc
Description
Summary:This paper presents a new method to perform sea/ice discrimination in single-pass ERS-2 scatterometer data. Existing methods are 1rst reviewed and compared in a consistent framework. Next, the ice probability according to the individual existing methods is learned through the use of a neural network. Finally, the individual criteria are combined together in order to increase the sea-ice discrimination accuracy. The proposed method is shown to provide an acceptable performance even on single-pass data, i.e., without requiring temporal averaging

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